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Senior Machine Learning Engineer

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Summary

Senior ML Engineer owning backend engineering strategy for an ML platform, building scalable pipelines for real-time analytics, and managing the full model deployment lifecycle using Docker, ACR, and PySpark.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do?

ØOwn the backend engineering strategy for the platform, ensuring repos, pipelines, and modular components are structured for scalable integration with software applications and visualization layers
ØLead the entire deployment lifecycle, from model training to deployment and monitoring on devices
ØDevelop, and maintain a scalable ML pipeline that enables real-time analytics for Test & Learn experimentation across business functions
ØOptimize and containerize models using Docker, and Azure Container Registry (ACR) etc. to ensure efficient execution in constrained environments. PySpark deep understanding is a must.
ØOwn and manage the GitHub repository, ensuring structured, well-documented, and modularized code for seamless deployments
ØEstablish robust CI/CD pipelines for continuous integration and deployment of models and services
ØImplement observability layers for data, feature, inference, and pipeline health (e.g., logging, monitoring, alerting), ensuring reliable and quick feedback loops
ØEnsure compliance with security and governance best practices for data and model deployment in centralized data environments
ØCollaborate with product and software teams to ensure backend architecture seamlessly integrates with frontend

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